Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/9671
DC FieldValueLanguage
dc.contributor.authorDr. LIU Jianwen, Kaceyen_US
dc.contributor.authorYin, Haoen_US
dc.date.accessioned2024-04-29T06:21:35Z-
dc.date.available2024-04-29T06:21:35Z-
dc.date.issued2024-
dc.identifier.citationLiu, J., & Yin, H. (2024 Jan 4). Examining gendered bias in AI Translation: A corpus-based study of ChatGPT’s translation of the second sex. International Conference of New Frontiers in Techno-Humanities 2024, Hong Kong.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11861/9671-
dc.language.isoenen_US
dc.titleExamining gendered bias in AI Translation: A corpus-based study of ChatGPT’s translation of the second sexen_US
dc.typeConference Paperen_US
dc.relation.conferenceInternational Conference of New Frontiers in Techno-Humanities 2024en_US
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of English Language and Literature-
Appears in Collections:English Language & Literature - Publication
Show simple item record

Page view(s)

36
Last Week
0
Last month
checked on Nov 21, 2024

Google ScholarTM

Impact Indices

PlumX

Metrics


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.